HMCan: A method for detecting chromatin modifications in cancer samples using ChIP-seq data

Handle URI:
http://hdl.handle.net/10754/325440
Title:
HMCan: A method for detecting chromatin modifications in cancer samples using ChIP-seq data
Authors:
Ashoor, Haitham; Hérault, Aurélie; Kamoun, Aurélie; Radvanyi, François; Bajic, Vladimir B. ( 0000-0001-5435-4750 ) ; Barillot, Emmanuel; Boeva, Valentina
Abstract:
Motivation: Cancer cells are often characterized by epigenetic changes, which include aberrant histone modifications. In particular, local or regional epigenetic silencing is a common mechanism in cancer for silencing expression of tumor suppressor genes. Though several tools have been created to enable detection of histone marks in ChIP-seq data from normal samples, it is unclear whether these tools can be efficiently applied to ChIP-seq data generated from cancer samples. Indeed, cancer genomes are often characterized by frequent copy number alterations: gains and losses of large regions of chromosomal material. Copy number alterations may create a substantial statistical bias in the evaluation of histone mark signal enrichment and result in underdetection of the signal in the regions of loss and overdetection of the signal in the regions of gain. Results: We present HMCan (Histone modifications in cancer), a tool specially designed to analyze histone modification ChIP-seq data produced from cancer genomes. HMCan corrects for the GC-content and copy number bias and then applies Hidden Markov Models to detect the signal from the corrected data. On simulated data, HMCan outperformed several commonly used tools developed to analyze histone modification data produced from genomes without copy number alterations. HMCan also showed superior results on a ChIP-seq dataset generated for the repressive histone mark H3K27me3 in a bladder cancer cell line. HMCan predictions matched well with experimental data (qPCR validated regions) and included, for example, the previously detected H3K27me3 mark in the promoter of the DLEC1 gene, missed by other tools we tested. The Author 2013. Published by Oxford University Press. All rights reserved.
KAUST Department:
Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Ashoor H, Herault A, Kamoun A, Radvanyi F, Bajic VB, et al. (2013) HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data. Bioinformatics 29: 2979-2986. doi:10.1093/bioinformatics/btt524.
Publisher:
Oxford University Press
Journal:
Bioinformatics
Issue Date:
9-Sep-2013
DOI:
10.1093/bioinformatics/btt524
PubMed ID:
24021381
PubMed Central ID:
PMC3834794
Type:
Article
ISSN:
13674803
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAshoor, Haithamen
dc.contributor.authorHérault, Aurélieen
dc.contributor.authorKamoun, Aurélieen
dc.contributor.authorRadvanyi, Françoisen
dc.contributor.authorBajic, Vladimir B.en
dc.contributor.authorBarillot, Emmanuelen
dc.contributor.authorBoeva, Valentinaen
dc.date.accessioned2014-08-27T09:51:26Z-
dc.date.available2014-08-27T09:51:26Z-
dc.date.issued2013-09-09en
dc.identifier.citationAshoor H, Herault A, Kamoun A, Radvanyi F, Bajic VB, et al. (2013) HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data. Bioinformatics 29: 2979-2986. doi:10.1093/bioinformatics/btt524.en
dc.identifier.issn13674803en
dc.identifier.pmid24021381en
dc.identifier.doi10.1093/bioinformatics/btt524en
dc.identifier.urihttp://hdl.handle.net/10754/325440en
dc.description.abstractMotivation: Cancer cells are often characterized by epigenetic changes, which include aberrant histone modifications. In particular, local or regional epigenetic silencing is a common mechanism in cancer for silencing expression of tumor suppressor genes. Though several tools have been created to enable detection of histone marks in ChIP-seq data from normal samples, it is unclear whether these tools can be efficiently applied to ChIP-seq data generated from cancer samples. Indeed, cancer genomes are often characterized by frequent copy number alterations: gains and losses of large regions of chromosomal material. Copy number alterations may create a substantial statistical bias in the evaluation of histone mark signal enrichment and result in underdetection of the signal in the regions of loss and overdetection of the signal in the regions of gain. Results: We present HMCan (Histone modifications in cancer), a tool specially designed to analyze histone modification ChIP-seq data produced from cancer genomes. HMCan corrects for the GC-content and copy number bias and then applies Hidden Markov Models to detect the signal from the corrected data. On simulated data, HMCan outperformed several commonly used tools developed to analyze histone modification data produced from genomes without copy number alterations. HMCan also showed superior results on a ChIP-seq dataset generated for the repressive histone mark H3K27me3 in a bladder cancer cell line. HMCan predictions matched well with experimental data (qPCR validated regions) and included, for example, the previously detected H3K27me3 mark in the promoter of the DLEC1 gene, missed by other tools we tested. The Author 2013. Published by Oxford University Press. All rights reserved.en
dc.language.isoenen
dc.publisherOxford University Pressen
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjecthistoneen
dc.subjectbladder tumoren
dc.subjectchromatin assembly and disassemblyen
dc.subjectchromatin immunoprecipitationen
dc.subjectcomputer programen
dc.subjectcomputer simulationen
dc.subjectcopy number variationen
dc.subjectDNA base compositionen
dc.subjectDNA microarrayen
dc.subjectgenetic epigenesisen
dc.subjectgeneticsen
dc.subjecthuman genomeen
dc.subjectmetabolismen
dc.subjectmethodologyen
dc.subjectprobabilityen
dc.subjectpromoter regionen
dc.subjectprotein processingen
dc.subjectBase Compositionen
dc.subjectChromatin Assembly and Disassemblyen
dc.subjectChromatin Immunoprecipitationen
dc.subjectComputer Simulationen
dc.subjectDNA Copy Number Variationsen
dc.subjectEpigenesis, Geneticen
dc.subjectGenome, Humanen
dc.subjectHistonesen
dc.subjectMarkov Chainsen
dc.subjectOligonucleotide Array Sequence Analysisen
dc.subjectPromoter Regions, Geneticen
dc.subjectProtein Processing, Post-Translationalen
dc.subjectSoftwareen
dc.subjectUrinary Bladder Neoplasmsen
dc.titleHMCan: A method for detecting chromatin modifications in cancer samples using ChIP-seq dataen
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalBioinformaticsen
dc.identifier.pmcidPMC3834794en
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionInstitut Curie, 75248 Paris Cedex 05, Franceen
dc.contributor.institutionINSERM, U900, Bioinformatics and Computational Systems Biology of Cancer, Franceen
dc.contributor.institutionMines ParisTech, Fontainebleau 77300, Franceen
dc.contributor.institutionUMR 144 CNRS, Subcellular Structure and Cellular Dynamics, Franceen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorAshoor, Haithamen
kaust.authorBajic, Vladimir B.en

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